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    Rapid determination of anti-tuberculosis drug resistance from whole-genome sequences

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    Type
    Article
    Authors
    Coll, Francesc cc
    McNerney, Ruth cc
    Preston, Mark D
    Guerra-Assunção, José Afonso
    Warry, Andrew
    Hill-Cawthorne, Grant A. cc
    Mallard, Kim
    Nair, Mridul
    Miranda, Anabela
    Alves, Adriana
    Perdigão, João cc
    Viveiros, Miguel cc
    Portugal, Isabel
    Hasan, Zahra cc
    Hasan, Rumina
    Glynn, Judith R. cc
    Martin, Nigel
    Pain, Arnab cc
    Clark, Taane G. cc
    KAUST Department
    Biological and Environmental Sciences and Engineering (BESE) Division
    Bioscience Program
    Computational Bioscience Research Center (CBRC)
    Pathogen Genomics Laboratory
    Date
    2015-05-27
    Online Publication Date
    2015-05-27
    Print Publication Date
    2015-12
    Permanent link to this record
    http://hdl.handle.net/10754/556149
    
    Metadata
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    Abstract
    Mycobacterium tuberculosis drug resistance (DR) challenges effective tuberculosis disease control. Current molecular tests examine limited numbers of mutations, and although whole genome sequencing approaches could fully characterise DR, data complexity has restricted their clinical application. A library (1,325 mutations) predictive of DR for 15 anti-tuberculosis drugs was compiled and validated for 11 of them using genomic-phenotypic data from 792 strains. A rapid online ‘TB-Profiler’ tool was developed to report DR and strain-type profiles directly from raw sequences. Using our DR mutation library, in silico diagnostic accuracy was superior to some commercial diagnostics and alternative databases. The library will facilitate sequence-based drug-susceptibility testing.
    Citation
    Rapid determination of anti-tuberculosis drug resistance from whole-genome sequences 2015, 7 (1) Genome Medicine
    Publisher
    Springer Nature
    Journal
    Genome Medicine
    DOI
    10.1186/s13073-015-0164-0
    PubMed ID
    26019726
    PubMed Central ID
    PMC4446134
    Additional Links
    http://genomemedicine.com/content/7/1/51
    ae974a485f413a2113503eed53cd6c53
    10.1186/s13073-015-0164-0
    Scopus Count
    Collections
    Articles; Biological and Environmental Sciences and Engineering (BESE) Division; Bioscience Program; Computational Bioscience Research Center (CBRC)

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